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John Wooden in 1997 [63] “Success is a peace of mind that is a direct result of self-satisfaction in knowing you did your best to become the best that you are capable of becoming”

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Process over Product

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Miller_2017_Is the Educational Technology Revolution Losing Steam What Academic Leaders Can Do to Keep Us Moving Forward

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The most dangerous people in Education are the people with Learning Science degrees and the English Department. Cash me outside. :)

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I reflected a lot on the chart on the most employable skills of graduates in this reading. As a former ELA teacher and AI dabbler, I have watched my job become irrelevant 5-6 times over the last three years. In certain ways, I have also watched my job become the most relevant in three years.

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Upgrade Your Teaching: Understanding by Design Meets Neuroscience

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How can educators leverage neuroscience research about how the human brain learns? How can we use this information to improve curriculum, instruction, and assessment so our students achieve deep learn

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How well do students learn when a lesson is mainly in PowerPoint? Henrik Berger Jørgensen, CC BY-NC-ND

For a brief period in the history of teaching, using PowerPoint automatically qualified you as a tech-savvy professor - an innovator who wouldn't settle for the usual combination of staticky black-and-white overhead films and hand-scrawled chalkboard notes.

Now, it's hard to believe that PowerPoint was once considered innovative by anyone. Popular criticism includes everything from tongue-in-cheek comments about death by PowerPoint to serious claims that it fundamentally degrades how we think and communicate.

But much of today's college instruction isn't in face-to-face classrooms, a setting in which PowerPoint was traditionally used. It's in the burgeoning field of online learning.

So if more learning is moving online, does that mean that teaching with PowerPoint is becoming a thing of the past?

Surprisingly, the answer is no.

Passive learning through PowerPoint?

Even though there's little research that directly addresses whether PowerPoint affects learning in college students, critics have questioned its value in educational settings.

Some ask whether PowerPoint might indirectly undermine the quality of teaching by reinforcing a passive learning approach.

We know that lecturing is less effective than alternative methods. It therefore makes sense for teachers in face-to-face classrooms to question how much of their class time ought to be spent on slideshows.

But the fact is "slideshows" remain a popular method for presenting content in today's online courses.

Technically, these are often not PowerPoints, but decks generated using other types of specialized programs.

And they may differ from standard in-class PowerPoint presentations in important ways.

For example, taking advantage of the increased flexibility of the online environment, they give students more control over how quickly to go through the material and when to backtrack. They can also have more interactive features, such as quizzes, that ask students to apply material while they are learning it.

Even so, the basic - and flawed - idea is the same: put the material in front of students, and learning will happen.

What's wrong with slideshows in online courses

As a psychologist specializing in teaching techniques and course design, when I talk to faculty about teaching effectively with technology, I sometimes tell them to follow the ABS principle: anything but slideshows.

I'm only half-kidding with that blanket statement.

After all, we learn with the same brains in online environments as we do face-to-face; the principles of learning don't change just because the medium changes. And today's learning theorists agree: active involvement trumps passive viewing.

Students need to grapple with challenging problems, practice skills, discuss and defend viewpoints. But for this kind of active learning to happen, instructors need to ensure they do not rely too heavily on slides.

There are alternatives: simulations, problem-based learning, even educational games are all proven methods for drawing students in. They also transplant well into online learning.

Using slideshows the right way

So do slideshows have any place in a well-designed online course? Possibly.

They can be used strategically for things they are best at: giving students an overview of new material, or providing a refresher on concepts students will need for an upcoming activity.

Slides are also great for for integrating visual illustrations. This is important because visuals - diagrams, figures, photos and the like - have a powerful impact on learning.

Visual information is almost always more memorable than sound, text or other modalities.

This isn't because of the now-debunked idea that some people are "visual learners," but more likely stems from how the brain codes images. There are separate systems for representing verbal and visual information in the brain. When we save information in both places, it is easier to recall.

Teachers don't have to stick with static images, either. Even basic animations can illuminate conceptual relationships - such as cause and effect, or the unfolding of a process over time - in ways that text can't.

Furthermore, as University of California, Santa Barbara researcher Richard Mayer has discovered, visuals and the spoken word pair up in powerful ways, so that audio plus visuals produce better learning than either alone.

Research also tells teachers some things not to do with visuals. Instructors should avoid purely decorative graphics, as these can actually hamper learning.

They should also eschew reading text verbatim, instead using a conversational, natural speaking style for voiceovers and verbal explanations.

What this means in the larger context of online learning

In sum, slideshows can be a useful part of online instruction, when used for the right things and designed in the right way. But they shouldn't be the main, or the only, method of instruction - any more than lectures should dominate face-to-face classes.

But it's not just instructors who need to hear this message.

Publishing and educational technology companies, who provide many of the tools that educators rely on, can do more to develop products that push beyond familiar formulas and draw on the latest learning science.

We need tools that make it easy to create assignments that ask students to apply what they have learned, in scenarios that are as realistic and challenging as possible.

These learning tools also need to be adaptive, adjusting the material and pace to the individual learner. This kind of educational technology does exist, but far more can be done to expand the available options.

Teaching in the age of technology comes with its own set of opportunities as well as challenges. And online education presents educators and tech developers with a rare opportunity to fundamentally rethink what we do.

Will we use it to explore new avenues for learning, or will we fall back on the the same old techniques that don't work well in face-to-face classrooms?

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Learning from PowerPoint: is it time for teachers to move on?

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Slideshows, when designed right, can be a useful part of online instruction. But they shouldn't be the main, or the only, method of instruction.

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This is why we need to frame AI as a short-term memory and task solution. Not a learning experience solution.

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This report arises from Science of Learning Fellowships funded by the International Brain Research Organization (IBRO) in partnership with the International Bureau of Education (IBE) of the United Nations Educational, Scientific and Cultural Organization (UNESCO). The IBRO/IBE-UNESCO Science of Learning Fellowship aims to support and translate key neuroscience research on learning and the brain to educators, policy makers, and governments.
Executive summary

Learning and memory are necessarily linked in the brain. You have only learnt something when it is coded in some form of memory for recall or use as a skill in the future. Neuroscience considers learning the same as acquiring or strengthening information in memory.

Memory is not a single thing in the brain. There are different forms of memory for facts, skills, and events of our life that involve different areas distributed across the brain.

Knowledge is thought to be coded in the brain in an interconnected network, with similar or associated items and concepts being more strongly connected. Recall or retrieval of some fact, memory, or piece of knowledge will spread activation to help recall of other similar and associated memories or knowledge.

Our brain, therefore, learns by making and strengthening connections between things in memory by association and context.

Learning and memory in the brain
If we define learning broadly as the acquisition of knowledge or skills (either through instruction, study, or experience), then the acquired knowledge or skills must be stored somehow in the brain for recall and use later. This, of course, is the role of memory. Therefore, learning and memory are closely linked in the brain.

Memory is not only a single thing in the brain. Rather, there are several different forms of memory, each with different processes that rely on different areas distributed across the brain. We see this clearly in people who damage particular areas of the brain and have different types of memory loss.

One very famous case, from whom we have learnt an enormous amount about memory and the brain, is a man called Henry Molaison (known as HM) ¹. HM had severe epilepsy and underwent a radical new surgery in 1953 to remove part of his brain known as the hippocampus. We know that the hippocampus is important for memory and learning, but it was also part of the area that was causing HM's epilepsy. The surgery was very successful for controlling HM's epilepsy, but unfortunately left him with very severe memory problems (see Ref. ² for classic and recent advances in understanding amnesia).

HM's main problem was that he could not make any new memories, and so he could not remember anything from after the time of his surgery. Even when introduced to someone new, if they were to leave the room and come back a few minutes later, HM would not remember having ever met them before. Every moment in his life after his surgery was new to him.

HM could not learn new words, faces, or facts because he could not form the memories to hold them. Interestingly, HM could recall events and knowledge that he had learnt from before the time of his surgery. This tells us that the processes in the brain for holding and recalling memories or knowledge are separate from the brain processes for learning and acquiring memories or knowledge.

HM could also learn new skills such as writing or tracing shapes in reverse while watching only in a mirror. He would improve day-by-day as he practiced these tasks, although he could never consciously remember having done the tasks before. This tells us that the memory for learning new skills with practice is separate from the memory for learning facts and knowledge for conscious recall.

This gives us several important definitions for different forms of memory. Firstly, we make a distinction between long-term and short-term memory. Short-term or working memory relies on the frontal lobes of the brain and is what we use when keeping things in mind immediately while working on a task or problem. Long-term memory is really what we consider when thinking about learning. It is memory for knowledge or skills that is acquired, stored, and recalled for use sometime in the future and has several important divisions. Refer to Ref. ³ for more information on the differences between short-term and long-term memory.
Knowledge versus skills: Declarative and procedural memory
Long-term memory is divided into declarative memory for facts and knowledge that we can consciously retrieve and "declare," and procedural memory for unconscious or automatic skills that we acquire such as how to ride a bicycle or how to make the finger movements necessary to form readable characters when writing.

When learning to read, we do not think about how to decipher the patterns of ink on the page (procedural memory), but we do consciously retrieve the meanings of the words (declarative memory). Maths also requires the use of procedural and declarative memory. Number fluency requires understanding of place value and the relationship between operations when solving equations (procedural memory), whereas number facts are basic equations learnt off by heart, such as 3 x 4 = 12 (declarative memory).
Facts versus events: Semantic and episodic memory
Our conscious knowledge, or declarative memory, is further divided into semantic memory for basic facts, meanings of words, and concepts, and episodic memory for recalling life events and episodes such as what we did on our last birthday.

Learning facts (semantic memory) can also be associated with the episode of having learnt the information. Studies have shown that recall of facts is better when retrieval occurs in the same or replicated environment where the content was learnt (or encoded) 4,5.
Knowledge coded in the brain: Grandmother cells
With these basic definitions of learning and memory, we can now look at theories about how the brain codes and stores knowledge. The brain is made up of brain cells known as neurons that are massively interconnected through links known as synapses. A single neuron in the brain may be connected to hundreds or thousands of other neurons through its synapses. With about 86 billion neurons in the brain, we estimate that there are 150 trillion or so connections, or synapses. It is this massive network of interconnections that gives the brain its immense computational power.

These connections between neurons through the synapses are continually changing with learning and experience. Learning in the brain is all about making and strengthening connections between brain cells.

So how is knowledge coded in the brain? In the late 1960s, the neuroscientist Jerry Lettvin famously wrote about grandmother cells, neurons in the brain that uniquely represent your grandmother ⁶. These brain cells theoretically fire their signal, communicating to the rest of your brain, whenever you encounter or think of your grandmother, whether in person or photograph, imagined or remembered, or even by name or another abstract form. These cells therefore represent or code the concept that is your grandmother in your brain. If we could somehow find all of the grandmother cells in your brain and remove them, you would completely lose all memory of your grandmother. However, this does not mean that there are cells that do nothing except code for your grandmother.

While this is a quirky example, the theory is that meaningful concepts are uniquely represented or coded in the brain by unique sets of neurons. Since we have billions of neurons within the interconnected network of cells that make up the brain, we can code billions of concepts or memories within this network, each represented by a unique pattern across different sets of neurons.

Scientific evidence for grandmother cells took a long time, but in 2005 a group of researchers managed to measure activity from single neurons in the brains of some patients undergoing surgery for treatment of their epilepsy. What the researchers found were not grandmother cells, but Jennifer Aniston cells-neurons that fired their signal to the rest of the brain specifically when the patient saw pictures of the famous actress Jennifer Aniston! Notably, this network of cells did not respond to pictures of other famous or familiar people, buildings, or objects. However, it is also important to emphasise that when researchers find a neuron firing to a particular concept, this neuron is part of a network of cells. In this context, the network of cells in question specifically fired their signal, communicating to the rest of the brain, only for Jennifer Aniston. This fits with the theory that specific concepts, such as your grandmother or Jennifer Aniston, are coded by unique patterns of activity in different sets of neurons in the brain (refer to Ref. 7 for conceptual clarification).
The importance of connections: Learning by association and context
So we have individual concepts, memories, or pieces of knowledge, each coded in the brain in unique sets of neurons. Importantly, these concepts are linked together in the interconnected network of the brain through the synapses, or connections between neurons. It is these connections via the synapses that are constantly changing in our brain with learning and experience.

Do you have a particular memory or idea that always pops into your head automatically when you see or think about a specific place, person, object, or event in your life? Perhaps there is a particular smell or food or place that always reminds you of your grandmother? This is because of the connections that have formed between your grandmother cells and other cells frequently associated with your grandmother. Encountering one, such as the smell of lavender, will lead to spreading activation to other associated concepts, such as your grandmother, and recollections of your grandmother pop into your mind. It is the connections that code the memory.

Another example, if I ask you what is the capital city of France, you will probably also think of red, white, and blue, cheese, and croissants, or personal memories of events in your life related to France and Paris. Activation will spread to all things that you have personally learned that are associated with France, leading to automatic or easier recall of those associated memories or pieces of knowledge.

The well-known phrase "neurons that fire together wire together" describes learning by making and strengthening connections between associated items, known as Hebbian learning. When two connected neurons fire their signal at the same time, the connection between them is strengthened so that, in the future, activation of one is more likely to lead automatically to activation of the other.

For example, if you encounter the smell of lavender and your grandmother at the same time, your lavender cells and your grandmother cells will form a connection. That connection will be strengthened the more often you encounter those two together. In the future, when the two share a strong connection, activation of one will lead to automatic or easier activation of the other. In psychology, the same idea is known as associative learning, whereby items that are commonly encountered together lead to stronger association so that recall of one leads to automatic or easier recall of the other in the future. This process of making and strengthening connections between neurons that are encountered and activated together is thought to represent most learning in the brain.

In education, this concept can apply from very simple to very complex knowledge. If you ask a preschool child what is a cat, they may say something like "a small animal with fur that says meow," showing that their concept of cat is encoded by its associated features (animal, fur, meow). Similarly, if you ask a university political science student what is a socialist system of government, they are likely to reply in terms of associated features or concepts.

Knowledge is therefore thought to be coded in the brain by unique patterns of activity across different sets of neurons that are linked and spread activation to other associated concepts, memories, or pieces of knowledge. Learning involves making or strengthening the connections between concepts as they are encountered or recalled together.

So now you have been introduced to grandmother cells and Jennifer Aniston cells, it is likely that your neurons representing Jennifer Aniston and those representing your grandmother are now associated in your brain and share a connection. Perhaps next time you see Jennifer Aniston on the television, you might automatically think of your grandmother!
The importance of recall: Consolidation of learning
By Hebbian learning, neurons firing together wiring together, the recall of associated concepts will also involve activation of the neurons representing those concepts at the same time, further strengthening the connection between them. This has very important implications for recall and consolidation of learning.

For example, if I ask you "What is the name of the theoretical cells that were supported by the discovery of Jennifer Aniston cells in the brain?" hopefully you will recall grandmother cells. Now, again, your neurons representing Jennifer Aniston and those representing your grandmother have been activated together, purely through recall, and the connection between them will be further strengthened.

Similarly, a political science student asked to describe a socialist system of government, and given the opportunity for discussion and feedback with a teacher or peers, will further strengthen the connections between associated concepts, as they are activated together, consolidating their learning.
Implications for education and learning
Two immediate implications of this understanding of learning and memory in the brain are:

Rote learning of disconnected facts is difficult because it is generally not the way the brain learns. Rather, the brain learns by making and strengthening connections between associated concepts so that learning in context and by linking and association with related knowledge will be more effective. This is seen very clearly in the benefit of using mnemonics that can greatly help learning by creating meaningful associations between items. Using the phrase "never believe a lie" is an example of a mnemonic to remember the correct order of the 'i' and the 'e' in the word 'believe.'

Activities that promote recall or reevaluation of knowledge are highly beneficial for learning by reinforcing and further strengthening the connections between associated items that are recalled together. Examination and assessment should therefore be structured in a way that aids the recall of associated concepts, reinforcing the neural connections between these items and further consolidating learning. In this way, appropriately structured examination can be an integral part of learning itself. How much should we facilitate recall during an exam and how much should we challenge it by not giving clues?

References

1. Squire, L. The legacy of Patient H.M. for neuroscience. Neuron 61, 6-9 (2009).

2. Allen, R. Classic and recent advances in understanding amnesia. F1000Research 7, 331 (2018).

3. Norris, D. Short-term memory and long-term memory are still different. Psychological Bulletin 143, 992-1009 (2017).

4. deBettencourt, M., Turk-Browne, N. & Norman, K. Neurofeedback helps to reveal a relationship between context reinstatement and memory retrieval. NeuroImage 200, 292-301 (2018).

5. Smith, S. A comparison of two techniques for reducing context-dependent forgetting. Memory & Cognition 12, 477-482 (1984).

6. Gross, C. Genealogy of the "Grandmother Cell." The Neuroscientist 8, 512-518 (2002).

7. Quian Quiroga, R. & Kreiman, G. Postscript: About grandmother cells and Jennifer Aniston neurons. Psychological Review 117, 297-299 (2010).

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IBE - Science of learning portal - Learning and memory: How the brain codes knowledge

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Learning in the brain is all about making and strengthening connections between brain cells called neurons. With about 86 billion neurons in the brain, it can be estimated that we have about 150 trillion or so connections, or synapses. It is this massive network of interconnections that gives the brain its immense computational power.

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I am deep in this world with my son. Fascinating what our brains do. I have heard people say that 3-4 is kinda what they'll be like at 15-17. This makes me optimistic. Also, big yikes!

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IBE — Science of learning portal — Affective Touch And Preschool Learning

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The IBE Science of learning portal features technical briefs on neuroscience topics for policy makers, practitioners, educators, parents and students.

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These strategies are really valuable. I am going to be coming back to this page a lot.

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Metacognitive thinking skills are important for instructors and students alike. This resource provides instructors with an overview of the what and why of metacognition and general "getting started" strategies for teaching for and with metacognition.

Metacognition is the CTL's programming theme for 2018 - 2019, and below you will find upcoming offerings that relate to this theme.

In this page:

Metacognition, sometimes described as "thinking about your own thinking," refers to knowledge about one's own thoughts and cognitive processes as well as the cognitive regulation involved in directing one's learning. Engaging in metacognition allows learners to recognize gaps in their knowledge or difficulty in acquiring new information, as well as to identify and integrate new knowledge into their existing cognitive framework.

The process of metacognition requires individuals to assess and monitor their learning, in addition to reflecting on their performance. Developing metacognitive skills can be as simple as asking students what they did to prepare for an exam, and whether, after seeing their exam performance, they would prepare differently for the next exam. This can encourage students to think about their preparation methods and whether those methods are appropriate or useful.

The terms used in the science of learning literature for the processes associated with metacognition are cognitive knowledge and cognitive regulation. Table 1 breaks down these two components of metacognition by naming attributes associated with each.

Table 1: Metacognitive Components and Their Attributes

Instructors/Learners know:

themselves as learners and factors affecting their cognition / how learning works.

learning strategies to manage their own cognition.

why and when to use a given learning strategy (e.g., space out studying over time).

Instructors/Learners know:

assess the task.

plan for and use appropriate strategies and resources.

monitor task performance.

evaluate processes and products of their learning and revise their goals and strategies accordingly.

Adapted from Emily Lai,"Metacognition: A Literature Review ," Research Report for Always Learning, Pearson: Assessment & Information Group; and informed by Ambrose et al. (2010) and Dunlosky and Metcalfe (2009).

The Center for Teaching and Learning encourages instructors to teach metacognitively. This means to teach " with and for metacognition." To teach with metacognition involves instructors "thinking about their own thinking regarding their teaching" (Hartman, 2001: 149). To teach for metacognition involves instructors thinking about how their instruction helps to elucidate learning and problem solving strategies to their students (Hartman, 2001).

What are the benefits of metacognitive skills for learners?
Learners with metacognitive skills are:

More self-aware as critical thinkers and problem solvers, enabling them to actively approach knowledge gaps and problems and to rely on themselves.

Able to monitor, plan, and control their mental processes.

Better able to assess the depth of their knowledge.

Able to transfer/apply their knowledge and skills to new situations.

Able to choose more effective learning strategies.

More likely to perform better academically.

What are the benefits of metacognitive skills for instructors?
Instructors who teach metacognitively / think about their teaching are:

More self-aware of their instructional capacities, and know what teaching strategies they rely upon, when and why these use these strategies, and how to use them effectively and inclusively.

Better able to regulate their instruction before, during, and after conducting a class session (i.e., to plan what and how to teach, monitor how lessons are going and make adjustments, and evaluate how a lesson went afterwards).

Better able to communicate, helping students understand the what, why, and how of their learning, which can lead to better learning outcomes.

Able to use their knowledge of students' metacognitive skills to plan instruction designed to improve students' metacognition and to create inclusive course climates.

The Center for Teaching and Learning has compiled the following list of research-supported practices for instructors interested in activating and developing students' metacognitive skills. Listed below are additional strategies for instructors looking to become more metacognitive in all facets of their teaching practice.

Teaching for metacognition - Metacognitive strategies that serve students and their learning:

Provide students with a list of simple questions they can ask themselves throughout the semester to make sure they are on track. Tanner (2012) provides an extensive list of the types of questions students can use to self-monitor their learning, their success, and their progress.

When introducing the syllabus, explicitly teach students how to engage in meaningful reflection on their learning and demonstrate how this reflection connects to their success, their self-awareness, and their regulation of their future learning.

Revisit this conversation after returning a major assignment or exam.

Build in class time for students to reflect on and assess their learning-individually and in collaboration with their peers. Ask students to write a 1-minute reflection paper at the end of a class session with the prompt: what is your main takeaway from today's class session?

Design homework assignments that ask students to focus on their learning process. This includes having students monitor progress, identify and correct mistakes, and plan next steps.

Following an exam, ask students to complete a self-assessment (also known as an "exam wrapper") in which they reflect on their performance, how they prepared for the exam, and what they would do differently as they prepare/study for the next exam. This self-assessment can be revisited prior to the next exam to remind students of their observations on how to better prepare themselves.

Model metacognitive processes for students OR
Make metacognitive processes visible to students

Think aloud as you solve a problem, read a text, write notes, or perform other disciplinary behaviors to model for students the steps you take.

Offer group office hours to encourage students to verbalize their learning processes and listen to others' approaches to reasoning and problem solving.

Provide structures to aid students in recognizing strengths and areas for improvement in their learning process.

Provide structures to guide students in creating implementable action plans for improvement.

Show students how to move stepwise from reflection to action.

Many platforms such as CourseWorks provide tools that students can use to keep up with their course work and monitor their progress.

Use the assessment tools in CourseWorks to help students self-monitor and self-evaluate.

Teaching with metacognition - Metacognitive strategies that serve the course and the instructor's teaching practice:

Set course and instructional objectives and milestones to measure progress and success.

Create an evaluation plan to periodically evaluate one's teaching and course design, set-up, and content.

Structure the course to provide time for students to give feedback on the course and teaching.

Use course and instructional objectives to measure progress.

Schedule mid-course feedback surveys with students.

Request a mid-course review (offered as a service for graduate students).

Review end-of-course evaluations and reflect on the changes that will be made to maximize student learning.

Set aside time before, during, and after a course to reflect on one's teaching practice, relationship with students, course climate and dynamics, as well as assumptions about the course material and its accessibility to students.

Reflect on course and teaching practice and revise goals and strategies for next iteration of course.

Metacognition and Memory Lab | Dr. Janet Metcalfe (Professor of Psychology and of Neurobiology and Behavior) runs a lab that focuses on how people use their metacognition to improve self-awareness and to guide their own learning and behavior. Dr. Metcalfe is author of Metacognition: A Textbook for Cognitive, Educational, Life Span & Applied Psychology (2009), co-authored with John Dunlosky.

In Fall 2018, the CTL and the Science of LEarning Research (SOLER) initiative co-organized the inaugural Science of Learning Symposium "Metacognition: From Research to Classroom" which brought together Columbia faculty, staff, graduate students, and experts in the science of learning to share the research on metacognition in learning, and to translate it into strategies that maximize student learning. View video recording of the event here.

During 2018 - 2019, the CTL will offer a variety of programs that focus on metacognition. Join us for the following Spring 2019 offerings:

For all instructors (graduate students and faculty):

Promoting Deep Learning through Metacognitive Activities

February 27, 2019 (Morningside) - Learn more and register here.

March 5, 2019 (CUIMC) - Learn more and register here.

Teachers' Lounge: Bridging the Expert/Novice Divide

February 19, 2019 - Learn more and register here.

Teachers' Lounge: Teaching Students How to Teach Themselves in a Discipline

March 26, 2019 - Learn more and register here.

For faculty:

Discussion-into-Practice: Student learning and metacognition faculty reading group

Each week faculty dive into the literature and explore metacognition by discussing an article or book chapter. Together participants consider how the research on metacognition could inform their practices. Join us for one, two, or all three sessions! Learn more and register here.

How Do Students Become Self-Directed Learners? | February 27, 2019 - CUIMC .

Learning From One's Own Errors and Those of Others | March 13, 2019 - CUIMC .

Improving Students' Learning with Effective Learning Techniques | March 27, 2019 - CUIMC .

For faculty consultations on teaching with and for metacognition, contact: ctlfaculty@columbia.edu

For consultations on using digital tools to support student learning and promote metacognition, contact the CTL Learning Designer assigned to your department or school.

For graduate students:

Language Lounge: Growth Mindset and Self-Motivation

February 26, 2019 - Learn more and register here.

Language Lounge: Guiding Language Learning Beyond the Classroom

April 2, 2019 - Learn more and register here. For graduate student consultations on teaching with and for metacognition, contact: ctlgrads@columbia.edu

Lai, E.R. (2011). Metacognition: A Literature Review. Pearson's Research Reports. Retrieved from https://images.pearsonassessments.com/images/tmrs/Metacognition_Literature_Review_Final.pdf

National Research Council (2000). How People Learn: Brain, Mind, Experience, and School . Expanded Edition . Washington, DC: The National Academies Press. https://doi.org/10.17226/9853

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Metacognitive thinking skills are important for instructors and students alike. This resource provides instructors with an overview of the what and why of metacognition and general "getting started" strategies for teaching for and with metacognition. Metacognition is the CTL's programming theme for 2018 - 2019, and below you will find upcoming offerings that relate to this theme.

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The Dos and Don'ts section of this is fire!

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Cite this

Brabeck, M., & Jeffrey, J. (2015, March 9). Practice for knowledge acquisition (not drill and kill). American Psychological Association. https://www.apa.org/education-career/k12/practice-acquisition

Designing activities with the goal of transferring knowledge

It doesn't matter what subject you teach, differences in students performance are affected by how much they engage in deliberate practice. Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as play or repetition.

Deliberate practice is not the same as rote repetition. Rote repetition - simply repeating a task - will not by itself improve performance. Deliberate practice involves attention, rehearsal and repetition and leads to new knowledge or skills that can later be developed into more complex knowledge and skills. Although other factors such as intelligence and motivation affect performance, practice is necessary if not sufficient for acquiring expertise (Campitelli & Gobet, 2011).

Define practice:

"Deliberate practice (DP) occurs when an individual intentionally repeats an activity in order to improve performance. The claim of the DP framework is that such behavior is necessary to achieve high levels of expert performance." (Campitelli & Gobet, 2011, p. 280).

"Deliberate practice consists of activities purposely designed to improve performance." (Gobet & Campitelli, 2007, p. 160).

Benefits of deliberate practice

Practice is important for teaching and learning in at least five ways:

1. Practice greatly increases the likelihood that students will permanently remember new information (Anderson, 2008).

2. Practice increases student facility or automaticity (learning to apply elements of knowledge automatically, without reflection). Automaticity is usually only achieved through extensive rehearsal and repetition. Automaticity frees up students cognitive resources to handle more challenging tasks (Brown & Bennett, 2002; Moors & De Houwer, 2006).

3. When students practice solving problems, they increase their ability to transfer practiced skills to new and more complex problems. This is true in childhood (Glover, Ronning, & Bruning, 1990) and adult years (Li, Schmiedek, Huxhold, Röcke, Smith, & Lindenberger, 2008).

4. Practice helps students acquire expertise in subject matter and, therefore, it helps to distinguish novices from experts in given subjects (Ericsson, Krampe, & Clemens, 1993)

5. Cognitive gains from practice often bring about motivation for more learning (Kalchman, Moss, & Case, 2001).

Teachers should think of practice not as rote repetition, but as deliberate, goal-directed rehearsal paired with reflection on problem-solving processes. For example, when teachers have students practice identifying phonemes, the ultimate goal is for students to read with fluency and comprehension. Although fluent reading may be too complex a task for beginning readers to tackle, the more manageable task of identifying phonemes may scaffold students learning to achieve the ultimate goal of reading. That is, teachers should always design practice activities with the goal of transferring knowledge to new and more complex problems in mind.

General recommendations for practice and instruction

Research (Anderson, 2008; Campitelli & Gobet, 2011; Ericsson, Krampe, & Clemens, 1993) suggests several conditions that must be in place in order for practice activities to be most effective in moving students closer to skillful performance. Each of these conditions can be met with carefully designed instruction:

Because practice requires intense, focused effort, students may not find it inherently enjoyable. Therefore, teachers can encourage students to practice more by pointing out every time that practice has actually improved their performance. Motivate your students to practice by:

Expressing confidence in students' ability to succeed in solving practice problems.

Designing activities that maximize opportunities for students to succeed.

Teachers should design practice tasks with students existing knowledge in mind. When students succeed at practice problems, the benefits of practice are maximized. But when students become frustrated with unrealistic or poorly designed practice problems, they often lose motivation, will not receive the full benefits of the practice they have done, and will be less motivated to attempt future practice problems.

Students receive the greatest benefits from practice when teachers provide them with timely and descriptive feedback.

Students should have repeated opportunities to practice a task through practicing other tasks like it.

What type of feedback is most effective?

Feedback is most effective when it contains descriptions of how students work meets performance criteria and what students can do to improve. This kind of descriptive feedback is more effective than feedback consisting of vague, general comments (e.g., "nice work or "needs improvement).

Feedback should also be focused on the learning process. That is, teachers should focus their feedback on helping students reflect on their problem solving skills, as well as on progress they have made.

Do's:

1. Vary practice activities.

2. Distribute practice over extended periods of time.

3. Provide clear instructions on performance expectations and criteria.

4. Before asking students to practice independently, model the problem-solving process that you expect students to use.

5. Break complex problems into their constituent elements, and have students practice on these smaller elements before asking them to solve complex problems independently.

6. Guide students through sample practice problems by using prompts that help them reflect on problem-solving strategies.

7. Provide students with fully completed sample problems as well as partially completed sample problems before asking them to apply new problem-solving strategies on their own.

8. Wait until students actually need more information to solve a complex problem before you give them more information. This strategy - known as "just-in-time instruction" - helps keep the amount of information that students must hold in their short-term memories to a manageable level as they practice (Linneman & Plake, 2006; Simkins & Maier, 2008).

9. Provide plenty of opportunities for students to practice applying problem-solving skills before you test them on their ability to use those skills.

Don'ts:

1. Don't ask students to practice complex problem solving without providing them with plenty of guidance and feedback.

2. Don't overload students by presenting information in redundant formats.

3. Don't give your students complex practice problems before they have the skills they need to succeed.

Research suggests that when teachers construct problems for students to practice, they should keep in mind the limitations of human memory.

Moving information to permanent storage is often explained as a multistore model of memory (Atkinson & Shiffrin, 1968; 1971; Baddeley, 1996; 2002). According to this model, our brains have three memory storage systems: sensory memory, short-term memory and long-term memory (Baddeley, 1996; 2002; Carlson, Sullivan, & Schneider, 1989). Learning occurs when we move information from working memory to long-term memory, and practice helps with this process.

Deliberate practice (sometimes called 'rehearsal') keeps the information in our short-term memory long enough for it to move to long-term memory. Once it is in long-term memory, it can be built upon to create more and more complex associations (Baddeley, 2002).

Most researchers agree that there are forms of Short-Term Memory (STM) for different modalities, such as visual STM, auditory STM and motor STM. For example, Baddeley (1992; 1996; 2002) suggests that short-term memory is a dynamic place where sounds and images are turned into verbal and pictorial models. STM is also thought to have a "central executive" that manages the information it is holding. This central executive also controls our awareness of that information (Baddeley, 2002).

The implication for teachers is that they should present material in multiple modalities. If a child who is learning to read hears a word, sees the word and a picture of the word, there will be more learning. The child can get the visual information from the visual STM and additional auditory information in the auditory STM. These two sensory sources of information supplement and complement one another (Liao, 2014). However, teachers must be careful not to have too much extraneous information in the classroom. Over stimulation can put too much demand on working memory (Pass & Kester, 2006).

Short-term or working memory

Working memory or short-term memory, is stored for very short periods of time - minutes at most. Information in our short-term memory is generally housed in the temporal lobe of the brain (the hippocampal region). It allows you to remember phone numbers and also information that comes from long-term memory right before you need to use it. Short-term memory is also the memory system that is used when we cram for a test at the last minute. Attention difficulties, distractions and overload of too much information all negatively impact our short-term memory and cause it to fail. We all have a limited ability to focus on too much stimuli at the same time, and if we don't process the information, we lose it. Practice helps us increase our ability to access information rapidly and automatically.

Practice also frees our brains to process more challenging information and problems. For example, if a child has memorized the multiplication table and can retrieve it automatically, working memory is freed to do more complicated computations.

Practice can improve children's working memory and enhance learning of academic skills, such as reading comprehension and mathematical reasoning (e.g., Dahlin, 2011; Gersten, Fuchs, Williams, & Baker, 2001; Holmes, Gathercole, & Dunning, 2009), verbal learning (Liao, Kronemer, Yau, Desmond, & Marvel, 2014) and motor skills (Gomes, Ugrinowitsch, Marinho, Shea, Raisbeck, & Benda, R., 2014).

And practice using visual spatial tasks can improve visual-spatial working memory (Melby-Lervag & Hulme, 2012; Shipstead, Redick, & Engle, 2012). Likewise, children can be taught a rehearsal or practice strategy to help them improve their reading comprehension (e.g., Gersten, Fuchs, Williams, & Baker, 2001; Rose, Cundick, & Higbee, 1983). Moreover, rehearsal is easier to learn and less demanding than other strategies (Turley-Ames & Whitfield, 2003).

Long-term memory

When working-memory is stored, it becomes long-term memory. Long-term memory is the depository of memories throughout the brain that results from the ongoing chemical processes that changes neuronal connections. The formation of long-term memories takes place over the span of days, weeks and in some cases years. As the memories are consolidated, neuron connections become more and more efficient, and in the process, connections that are no longer useful are discarded from lack of use.

Although the capacity of our long-term memory is apparently limitless (as far as we know, no one has ever stored all that the brain is capable of storing), working memory can typically hold only seven items (plus or minus 2) at any given time, and these items "decay" rapidly (Miller, 1956; Baddeley, 2002).

Research on the brains of rats has shown that relatively short periods of practice can enhance the plasticity of the brain and actually change its structure (Rioult-Pedotti, Friedman, Hess, & Donoghue, 1998). Brain imaging has shown that even a brief lesson on new words changes brain circuits (Allami, Brovelli, Hamzaoui, Regragui, Paulignan, & Boussaoud, 2014; Abdullaev & Posner, 1998; Raichle et al., 1994) and retrieval (Habib, Nyberg, & Tulving, 2003).

Experts and novices differ in the amount and structure of information stored in their long-term memories. These cognitive differences occur in large part because of differences in the amount of deliberate practice in which each has engaged (Cantor & Engle, 1993).

Extensive and deliberate practice makes it possible for students to access and apply increasingly complex information without explicitly thinking about it. In other words, it increases automaticity (see earlier discussion of automaticity) (Anderson, 2008; Case, 1985, 1991). Automaticity leaves students' working memories free to process new information (Kotovsky, Hayes, & Simon, 1985). Since working memory can be overloaded at any time, 'savings' from automaticity become very important. When there is too much information in our working memory it will fail, and the chemical processes that transfer information to our long-term memories also fail. Long-term learning is enhanced by a distribution process in which information is repeated, allowing time with time in between practice sessions, rather than crammed practice.

Reviews and tests are forms of practice that can improve learning. Tests (or quizzes) that are given immediately after a learning exercise give children opportunities to practice. Because learning is recent, students tend to do well on these tests. However, their success does not ensure long-term retention. Teachers can provide time during class to give students additional practice in taking tests. Some tests, such as tests with open-ended answers have been shown to enhance learning because they involve students in the "retrieval" of information from long-term memory. Tests are more effective when they are given at spaced intervals and when they are given frequently (Cull, 2000; Dempster; 1991; Rodriguez, Michael, 2004;Roediger & Karpicke, 2006).

Chunking information, or combining small bits together in short-term memory, is another strategy that students can use to increase their STM holding capacity. Although chunking gives a student more capacity in their STM, its usefulness depends on how much knowledge a person already has. The more knowledge one has on a topic, the more likely that one can "chunk" incoming information into larger and more meaningful chunks. This is why knowledge itself adds to one's ability to solve complex problems. Children who use chunking are more likely to be strategic about their learning. Teachers can help children become more strategic by explicitly teaching them strategies like chunking.

Example of chunking information

The following digits can be seen as a random list of numbers: 14921776. Random or meaningless information taxes the limited capacity of short-term memory (STM). However, if a student "chunks" the information into two dates (1492: Columbus discovered America; and 1776: the year the Declaration of Independence was signed) it is learned as 1492 1776. This leaves room in the short-term memory for more information.

Chunking allows several units of information to be compressed into a single meaningful unit or chunk (e.g., whereas a random number string above represents 8 discrete units to be stored in short-term memory (near its maximum capacity), the two meaningful dates represent only two chunks of information to be stored. This leaves space in the STM for more information to be held. And when more information is held in STM, there is more information available for transfer to long-term memory where it can be permanently stored (Gobet et al., 2001).

Chunking can develop experts' schema. Information stored in the brain in larger chunks of integrated concepts are known as "schemas." For example, a novice chess player who does not yet have complex schemas for chess playing has to devote his or her limited working memory to processing large amounts of information while playing (Anderson, 1996).

An expert, on the other hand, can easily access schemas from long-term memory (deGroot, 1966; Cantor & Engle, 1993). With practice, a novice player can construct chess-playing schemas and therefore increase the amount of information stored in long-term memory. In this way, practice accessing and applying knowledge helps one to transfer that knowledge into a "permastore" of long-term memory so that he or she can more efficiently utilize space available in the working memory (Elo, 1978; Kotovsky & Fallside, 1989).

Theories explaining expert performance

1. Many researchers (e.g., Ericsson et al., 1993; Baddeley, 2002) argue that differences in the amount of practice account for the majority of performance differences between individuals, resulting from differences in the amount and structure of knowledge stored in long-term memory.

2. Other researchers emphasize innate, genetic differences or talent as the main factor accounting for differences between expert and novice performance (Mosing, et.al., 2014; Plomin, DeFries, McClearn, & Rutter, 1997).

3. More recently, researchers have emphasized an interaction between innate and behavioral factors in accounting for differences in performance levels (Gobet & Campitelli, 2007).

Overall, the research supports the view that deliberate practice plays a role in performance differences and can reduce performance differences between individuals who are thought to possess talent and those who do not (Chase & Ericsson, 1981). See Gobet and Campitelli (2007), Mosing, et.al., (2014) and Macnamara, et.al., (2014) for a comprehensive review of this debate.

What can a teacher do to maximize the positive effect of practice?

When teachers assign students to complete practice problems that are structurally similar but different in surface features, it helps them discriminate between relevant and irrelevant information in a given problem. This outcome makes it more likely that students will be able to transfer knowledge gained from practice to new and more complex problems (Paas, 1992). As with all scaffolds, they should be diminished gradually as learners become increasingly more independent.

Students' problem-solving skills also increase when teachers distribute practice over time rather than "cramming" practice into short periods (Bahrick & Hall, 2005). Assignments involving practice are more effective when they are shorter, more frequent and distributed over longer periods of time (Cooper, 2007; Cooper, Robinson, & Patall, 2006; Epstein & Van Voorhis, 2010). This distributive effect is particularly important because it also makes it more likely that students will recall information over longer periods of time. Therefore, distributed practice helps students transfer information into their long-term memory.

Teachers should also have students begin homework during class. By doing so, teachers can monitor students to ensure they understand and can solve practice problems correctly before they practice independently. If teachers are unable to monitor this initial practice, they should explain to their students where they can obtain the information (textbooks, web sites, handouts, etc.) they need to complete the assigned practice problems correctly.

Reviews and tests are a form of practice that can improve learning. Tests provide opportunities for practice that enhance learning. Open-ended test questions also provide practice in retrieving information. Both reviews and tests are most effective when they are well spaced and frequent (Dempster, 1991).

Teachers can train students to reflect on their thinking when solving problems by providing them with lists of questions. This kind of "strategy instruction" helps students to construct schemas more efficiently by facilitating a metacognitive awareness of the problem-solving process. That is, students learn more about how they learn and this helps them with new learning.

Teachers can increase students' abilities to transfer existing problem-solving knowledge to new problems when they prompt students to deliberately reflect on problem-solving strategies they have used before. (Renkl, Stark, Gruber, & Mandl, 1998; Rosenshine & Meister, 1992; Stark, Mandl, Gruber, & Renkl., 2002).

Is homework always effective practice?

There is no question that homework can provide students with opportunities for practice but there are more and less effective homework assignments. Research on homework (Cooper, 2001, 2006; Epstein & Van Voorhis, 2010) suggests that the relationship between time spent on homework and students' academic achievement varies with grade level. When parental involvement is well structured it can also enhance the effectiveness of homework on learning (Epstein & Van Voorhis, 2010; Marzano & Pickering, 2007).

How much time should be spent on homework?

Although high school students appear to benefit from at least two hours of homework per night, there is little or no relationship between time spent on homework and academic achievement for young (grades 1-3) students (Marzano, & Pickering, 2007). Younger students may benefit more from supervised in-school practice than from homework. Middle school students may benefit from one to two hours of homework per night (Cooper, 2007).

Will practice activities negatively affect students' motivation? Aren't practice activities the same as "drill and kill" instruction?

Although deliberate practice is often confused with rote learning, researchers emphasize that there is a difference between mere repetition and deliberate practice. For practice to be effective, appropriate instruction, guided practice, as well as descriptive and timely feedback must all be present.

Does practice with "authentic" problems increase learning?

Due to their relevance, "authentic" problems or "real-life" problems may motivate students. However, the positive effect of practice is only realized when teachers provide instructional supports that address the limitations of students' working memories (Anderson, Reder, & Simon, 1996, 2000; Sweller, van Merrienboer, & Paas, 1998; van Merrienboer, Kirschner, & Kester, 2003). If there is cognitive overload and the working memory is taxed beyond its capacity, students will lose motivation even if a problem is highly relevant to them.

Although "authentic" practice problems sound like they would motivate students with their real-world context; they may also include too many variables at the same time. Students' working memories are thus required to manage too many bits of information, and many of these bits may not be directly involved with the construction of the desired schema (Sweller & Chandler, 1994).

Is there such a thing as too much practice?

Merely repeating a task will not automatically improve performance. Deliberate practice is most effective when it involves intense concentration, rehearsal and reflection. For that reason, students are more likely to benefit from frequent, short practice sessions than from long "cramming" sessions. Teachers can foster this meta-cognitive learning process by providing students with frequent opportunities to discuss their problem-solving strategies (National Research Council, 2005).

Even in early grades when students are acquiring foundational knowledge, practice should not be confused with rote learning. For example, phonics instruction is most effective when it is practiced alongside more complex skills like identifying main ideas in stories (National Institute of Child Health and Human Development, 2000).

Does practice work for all academic subjects?

Practice is correlated with student achievement across all developmental levels and across all subjects. NICHD's (2000) analysis of strategies for reading instruction suggests that several kinds of practice activities are beneficial to students. Phonemic awareness practice, phonics practice and read-aloud practice all showed significant positive effects on student achievement in the early grades. Teachers should always keep long-term goals in mind when they are designing practice activities. The ultimate purpose of phonics instruction is not for students to identify phonemes, but rather, to improve their reading comprehension. The goal of practice is to transfer acquired skills to new and more complex problems. Therefore, practice activities should always be designed with that transfer process in mind.

Studies in mathematics education show that practice is effective when teachers design appropriate practice problems, distribute them over time, and provide students with sufficient feedback. Practice is ineffective when it is not appropriately designed, not well distributed, and when adequate feedback is not provided.

Deliberate practice is also effective in learning complex skills from musical fluency to athletic expertise.

When does the strategy work?

All students benefit from well-designed, developmentally-appropriate deliberate practice activities. A meta-analysis (Macnamara, Hambrick, & Oswald, 2014) showed that the effects of deliberate practice are robust for games, music and sports, and modestly effective in education.

Deliberate practice can also provide a bridge over the gaps that exist between different achievement levels. Achievement gaps often exist because of unequal opportunities for students to engage in appropriate deliberate practice rather than unequal learning abilities. As children grow older, they become better able to benefit from instruction on appropriate strategies like rehearsal, reflection and "chunking" information.

Special populations benefit from practice activities that are designed to meet their needs (Chapman, & Mudar, 2014; Nunes, Barros, Evans, & Burman, 2014; Rose, Cundick, & Higbee, 1983). For example, research on children with language processing problems suggests that their difficulties are due to sensory perception rather than an inability to learn. One reason that language-learning impaired students have difficulty learning to read is that their phonemic recognition and spatial discrimination perceptions are impaired. Appropriate practice activities have been shown to help these students compensate for their difficulties (Merzenich et al., 1996). Cooper's (2001) examination of homework practice suggests that students with learning disabilities benefit most from short, skill-reinforcing activities that are carefully monitored (see also Marzano & Pickering, 2007).

Description of research on the use of practice activities with children with learning disabilities

An extensive meta-analysis of interventions for students with learning disabilities found that practice-drill-review instructional strategies were generally effective across academic subjects (Swanson, Hoskyn, & Lee, 1999). Another meta-analysis of inclusion settings found that time-on-task correlated with student achievement across subject areas (Brophy & Good, 1986). Therefore, practice activities appear to be a key factor in student achievement across grade levels, skill levels and academic domains.

In summary, well-designed practice activities result from careful planning where teachers:

Model problem-solving processes.

Design partially-completed examples on which students can practice.

Sequence activities logically.

Space practice activities appropriately.

Monitor student practice providing guidance and feedback.

Is practice effective across the age span?

Children grow more strategic as they get older. Younger children are less strategic - are less likely to rehearse, practice, or chunk spontaneously or to know how to do these things well. They are also less likely to monitor their own knowledge or to use metacognitive strategies. Younger children are less likely than older children to know what they need to rehearse or practice more. Therefore, teachers of younger children should introduce them to strategies such as rehearsal and practice, and in this way can help students improve their learning.

Deliberate practice is effective across all school age levels. Fundamental practice skills are more appropriate for earlier grades than it is for later grades. Teachers can focus younger students on the skills they will need later when they tackle more complex tasks. For example, phonemic awareness instruction is more effective for preschool students than for older elementary school students (NICHD, 2000), but it remains a skill that is very useful in later grades.

Teachers should design developmentally appropriate practice problems for students. Students' memories and attention spans develop with age (Gomez-Perez & Ostrosky-Solis, 2006; Lechuga, Moreno, Pelegrina, Gomez-Ariza, & Bajo, 2006). In general, older students have greater attention spans and greater memory capacity than younger students. This may account for developmental differences seen in the benefits of homework (Cooper, 2001; Muhlenbrook, Cooper, Nye, & Lindsay, 1999) and age differences in the amount of practice that learners engage in outside the classroom (Ericsson et al., 1993). Teachers should plan the type and amount of practice students are expected to do with these developmental differences in mind.

Research on expert performance shows that experts increase the amount of deliberate practice they engage in over time. For example, research by Ericsson and colleagues (1993) on expert violinists revealed that in early childhood they practiced no more than five hours per week. However, by their early twenties, they practiced around thirty hours per week. Because deliberate practice is so taxing, it should be balanced with sufficient periods of rest. Younger learners tire more quickly and lose their motivation to persist if they are not allowed sufficient rest (Ericsson et al., 1993; NICHD, 2000).

Elementary

Early elementary students benefit little or not at all from homework (Campitelli & Gobet, 2011; Cooper, 2001; Halford, Maybery, & Bain, 1986).

Expert violinists practiced fewer than 5 hours per week at the early childhood stage (Ericsson et al., 1993; Macnamara et al., 2014).

Research supports the idea that practice can help elementary students overcome processing deficits (Merzenich et al., 1996).

Practice with phonemic awareness has been shown to have a positive effect on reading outcomes in elementary readers through 6th grade. Effects were not as strong for disabled readers as they were for at-risk and normally progressing readers. The effects of phonemic-awareness instruction were strongest when it was provided in earlier grades (especially pre-K and kindergarten), in small group settings, in shorter training programs and to English-speaking students (NICHD, 2000).

Research suggests that systematic phonics instruction helps students learning to read. The effects of systematic phonics instruction were greater when it was provided in earlier grades (especially kindergarten and 1st grade) (Dahlin, 2011; Gersten, Fuchs, Williams, & Baker, 2001; NICHD, 2000).

A meta-analysis of intervention strategies for students with learning disabilities found that phonics instruction positively affects development of vocabulary, although the results on comprehension were unclear (Swanson et al., 1999). (The mean age for the study participants was 11; 78% of the studies targeted 9-14 year age range.).

Research suggests that repeated and guided-repeated oral reading strategies have a positive effect on reading performance through grade four, especially for non-impaired readers (Dahlin, 2011; Gersten, et al., 2001; Rose et al., 1983).

Swanson et al.'s (1999) meta-analysis suggests that "the teaching of whole language without due attention to decoding places LD children at greater risk than the use of more traditional programs" (p. 254).

Vocabulary instruction (both explicit and implicit) has a positive effect on vocabulary acquisition. Research indicates that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that reading comprehension strategy instruction (e.g., cognitive and meta-cognitive strategies) has a positive effect on reading comprehension and memory in grades 3-6. The effects were greater when strategy instruction was more intensive and when students were instructed in multiple strategies (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

Middle School

Middle school students may benefit from one to two hours of homework per night (Cooper, 2001; Campitelli & Gobet, 2011).

Research suggests that partial-task practice problems are more effective than whole-task practice problems for some 13 year-old math students. Partial-task practice lowered the processing demands on working memory for all students, but it only increased learning for students with low prior knowledge. Students with high prior knowledge benefited more from whole-task practice (Ayres, 2006).

Research suggests that when modeling problem-solving strategies, the use of worked examples is beneficial for middle school students' writing performance. As with Ayres' (2006) study, however, the positive effects were limited to low-performing students. The results suggested that "low-level" writers benefited from worked-example practice problems, while "high-level" writers benefited from "goal-free" practice problems.

Research suggests that the use of repeated and guided-repeated oral reading strategies positively affect students' reading performance. This is especially true for students with reading problems (NICHD, 2000).

Programs aimed at encouraging students to read more (e.g., self-selected, silent reading) yielded no significant positive effects on reading achievement (NICHD, 2000).

Swanson et al.'s (1999) meta-analysis suggests that "the teaching of whole language without due attention to decoding places LD children at greater risk than the use of more traditional programs" (p. 254).

Results that support the positive effects of vocabulary instruction (both explicit and implicit) on vocabulary acquisition indicate that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that reading-comprehension-strategy instruction (e.g., cognitive and meta-cognitive strategies) has a positive effect on reading comprehension and memory in grades 3-6. The effects were greater when strategy instruction was more intensive and when students were instructed on multiple strategies (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

High School

High school students appear to benefit from at least two hours of homework per night, (Campitelli & Gobet, 2011; Cooper, 2001).

Students may benefit from more practice with the transfer of component skills than from practicing whole-task transfer (Pollock, Chandler, & Sweller, 2002). Examples worked out in advance for students were more effective for algebra problem solving transfer than were conventional problems for 9th and 11th grade students (Sweller & Cooper, 1985).

Repeated and guided-repeated oral reading strategies positively affect reading performance. This is especially true for high school students with reading problems (NICHD, 2000).

Programs aimed at encouraging students to read more (e.g., self-selected, silent reading) yielded no significant positive effects on reading achievement (NICHD, 2000).

Although research supports a positive effect of vocabulary instruction (both explicit and implicit) on vocabulary acquisition in grades 9-11, few studies have been conducted at that level. Results that do exist suggest that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

Where can teachers get more information?

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51(4), 355-368. http://dx.doi.org/10.1037/0003-066X.51.4.355

Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school. Washington, D.C.: National Academy Press. ISBN 0-309-07036-8

Carver, S. M. & Klahr, D. (Eds.). (2001). Cognition and instruction: Twenty-five years of progress. Mahwah, NJ: Erlbaum.

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Practice for knowledge acquisition (not drill and kill)

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Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as work, play and rote repetition.

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Teacher prep and development is a space that I want to begin working in. I think this is where we are failing in NM.

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This is that Zen vibe. The five Skhandas+memory=the illusion of self. Yet, something in there is still learning...maybe. Maybe it's just all remembering.

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Great List of Principles. Mariette hooked this one up!